Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://code.google.com/p/rna-star/
Software performing alignment of high-throughput RNA-seq data. Aligns RNA-seq reads to reference genome using uncompressed suffix arrays.
Proper citation: STAR (RRID:SCR_004463) Copy
https://sites.google.com/site/jingyijli/SLIDE.zip
Software package that takes exon boundaries and RNA-Seq data as input to discern the set of mRNA isoforms that are most likely to present in an RNA-Seq sample. It is based on a linear model with a design matrix that models the sampling probability of RNA-Seq reads from different mRNA isoforms. To tackle the model unidentifiability issue, SLIDE uses a modified Lasso procedure for parameter estimation. Compared with deterministic isoform assembly algorithms (e.g., Cufflinks), SLIDE considers the stochastic aspects of RNA-Seq reads in exons from different isoforms and thus has increased power in detecting more novel isoforms. Another advantage of SLIDE is its flexibility of incorporating other transcriptomic data such as RACE, CAGE, and EST into its model to further increase isoform discovery accuracy. SLIDE can also work downstream of other RNA-Seq assembly algorithms to integrate newly discovered genes and exons. Besides isoform discovery, SLIDE sequentially uses the same linear model to estimate the abundance of discovered isoforms.
Proper citation: SLIDE (RRID:SCR_005137) Copy
http://compbio.cs.brown.edu/projects/gasv/
Software tool combining both paired read and read depth signals into probabilistic model which can analyze multiple alignments of reads. Used to find structural variation in both normal and cancer genomes using data from variety of next-generation sequencing platforms. Used to predict structural variants directly from aligned reads in SAM/BAM format.Combines read depth information along with discordant paired read mappings into single probabilistic model two common signals of structural variation. When multiple alignments of read are given, GASVPro utilizes Markov Chain Monte Carlo procedure to sample over the space of possible alignments.
Proper citation: GASVPro (RRID:SCR_005259) Copy
http://bioportal.bioontology.org/annotator
A Web service that annotates textual metadata (e.g. journal abstract) with relevant ontology concepts. NCBO uses this Web service to annotate resources in the NCBO Resource Index. They also provide this Web service as a stand-alone service for users. This Web service can be accessed through BioPortal or used directly in your software. Currently, the annotation workflow is based on syntactic concept recognition (using concept names and synonyms) and on a set of semantic expansion algorithms that leverage the semantics in ontologies (e.g., is_a relations). Their service methodology leverages ontologies to create annotations of raw text and returns them using semantic web standards.
Proper citation: NCBO Annotator (RRID:SCR_005329) Copy
http://bowtie-bio.sourceforge.net/index.shtml
Software ultrafast memory efficient tool for aligning sequencing reads. Bowtie is short read aligner.
Proper citation: Bowtie (RRID:SCR_005476) Copy
http://llama.mshri.on.ca/gofish/GoFishWelcome.html
Software program, available as a Java applet online or to download, allows the user to select a subset of Gene Ontology (GO) attributes, and ranks genes according to the probability of having all those attributes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: GoFish (RRID:SCR_005682) Copy
http://great.stanford.edu/public/html/splash.php
Data analysis service that predicts functions of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. The utility of GREAT extends to data generated for transcription-associated factors, open chromatin, localized epigenomic markers and similar functional data sets, and comparative genomics sets. Platform: Online tool
Proper citation: GREAT: Genomic Regions Enrichment of Annotations Tool (RRID:SCR_005807) Copy
Ratings or validation data are available for this resource
Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.
Proper citation: UCSC Genome Browser (RRID:SCR_005780) Copy
http://purl.bioontology.org/ontology/DOID
Comprehensive hierarchical controlled vocabulary for human disease representation.Open source ontology for integration of biomedical data associated with human disease. Disease Ontology database represents comprehensive knowledge base of inherited, developmental and acquired human diseases.
Proper citation: Human Disease Ontology (RRID:SCR_000476) Copy
http://www.broadinstitute.org/genome_bio/siphy/
Software that implements rigorous statistical tests to detect bases under selection from a multiple alignment data. It takes full advantage of deeply sequenced phylogenies to estimate both unlikely substitution patterns as well as slowdowns or accelerations in mutation rates. It can be applied as an Hidden Markov Model (HMM), in sliding windows, or to specific regions.
Proper citation: SiPhy (RRID:SCR_000564) Copy
https://bitbucket.org/dkessner/forqs
Software for forward-in-time population genetics simulation that tracks individual haplotype chunks as they recombine each generation. It also also models quantitative traits and selection on those traits.
Proper citation: forqs (RRID:SCR_000643) Copy
Computable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.
Proper citation: Gene Ontology (RRID:SCR_002811) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, Documented on March 24, 2014. A resource for gene expression studies, storing highly curated MIAME-compliant studies (i.e. experiments) employing a variety of technologies such as filter arrays, 2-channel microarrays, Affymetrix chips, SAGE, MPSS and RT-PCR. Data were available for querying and downloading based on the MGED ontology, publications or genes. Both public and private studies (the latter viewable only by users having appropriate logins and permissions) were available from this website. Specific details on protocols, biomaterials, study designs, etc., are collected through a user-friendly suite of web annotation forms. Software has been developed to generate MAGE-ML documents to enable easy export of studies stored in RAD to any other database accepting data in this format. RAD is part of a more general Genomics Unified Schema (http://gusdb.org), which includes a richly annotated gene index (http://allgenes.org), thus providing a platform that integrates genomic and transcriptomic data from multiple organisms. NOTE: Due to changes in technology and funding, the RAD website is no longer available. RAD as a schema is still very much active and incorporated in the GUS (Genomics Unified Schema) database system used by CBIL (EuPathDB, Beta Cell Genomics) and others. The schema for RAD can be viewed along with the other GUS namespaces through our Schema Browser.
Proper citation: RNA Abundance Database (RRID:SCR_002771) Copy
A disease / disorder relationships explorer and a sample of a map-oriented scientific work. It uses the Human Disease Network dataset and allows intuitive knowledge discovery by mapping its complexity. The Human Disease Network (official) dataset, a poster of the data and related book (Biology - The digital era, ISBN: 978-2-271-06779-1) are available. This kind of data has a network-like organization, and relations between elements are at least as important as the elements themselves. More data could be integrated to this prototype and could eventually bring closer phenotype and genotype. Results should be visual, but also printable. Creating posters can enhance collaborative work. It facilitates discussion and sharing of ideas about the data. This website initiative is an invitation to think about the benefits of networks exploration but above all it tries to outline future designs of scientific information systems.
Proper citation: Diseasome (RRID:SCR_002792) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. Integrated database of genomic, expression and protein data for Drosophila, Anopheles, C. elegans and other organisms. You can run flexible queries, export results and analyze lists of data. FlyMine presents data in categories, with each providing information on a particular type of data (for example Gene Expression or Protein Interactions). Template queries, as well as the QueryBuilder itself, allow you to perform searches that span data from more than one category. Advanced users can use a flexible query interface to construct their own data mining queries across the multiple integrated data sources, to modify existing template queries or to create your own template queries. Access our FlyMine data via our Application Programming Interface (API). We provide client libraries in the following languages: Perl, Python, Ruby and & Java API
Proper citation: FlyMine (RRID:SCR_002694) Copy
http://www.ebi.ac.uk/arrayexpress/
International functional genomics data collection generated from microarray or next-generation sequencing (NGS) platforms. Repository of functional genomics data supporting publications. Provides genes expression data for reuse to the research community where they can be queried and downloaded. Integrated with the Gene Expression Atlas and the sequence databases at the European Bioinformatics Institute. Contains a subset of curated and re-annotated Archive data which can be queried for individual gene expression under different biological conditions across experiments. Data collected to MIAME and MINSEQE standards. Data are submitted by users or are imported directly from the NCBI Gene Expression Omnibus.
Proper citation: ArrayExpress (RRID:SCR_002964) Copy
http://www.mybiosoftware.com/population-genetics/332
A tool for SNP Search and downloading with local management. It also offers flanking sequence downloading and automatic SNP filtering. It requires Windows and .NET Framework.
Proper citation: SNPHunter (RRID:SCR_002968) Copy
http://www.ncbi.nlm.nih.gov/lovd/home.php?select_db=OCRL
The Lowe Syndrome Mutation Database is now being maintained by the National Center for Biotechnology Information (NCBI) at the National Institutes of Health. A database of mutations causing Lowe syndrome. Information on new mutations may be submitted online. Lowe oculocerebrorenal syndrome is an X-linked disorder caused by mutations in the OCRL1 gene, which encodes a 105-kDa Golgi protein with phosphatidylinositol (4,5) bisphosphate 5-phosphatase activity. genetics
Proper citation: Lowes Syndrome Mutation Database (RRID:SCR_002907) Copy
http://insitu.fruitfly.org/cgi-bin/ex/insitu.pl
Database of embryonic expression patterns using a high throughput RNA in situ hybridization of the protein-coding genes identified in the Drosophila melanogaster genome with images and controlled vocabulary annotations. At the end of production pipeline gene expression patterns are documented by taking a large number of digital images of individual embryos. The quality and identity of the captured image data are verified by independently derived microarray time-course analysis of gene expression using Affymetrix GeneChip technology. Gene expression patterns are annotated with controlled vocabulary for developmental anatomy of Drosophila embryogenesis. Image, microarray and annotation data are stored in a modified version of Gene Ontology database and the entire dataset is available on the web in browsable and searchable form or MySQL dump can be downloaded. So far, they have examined expression of 7507 genes and documented them with 111184 digital photographs.
Proper citation: Patterns of Gene Expression in Drosophila Embryogenesis (RRID:SCR_002868) Copy
http://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi
A web interface to the Primer3 primer design program as an enhanced alternative for the CGI- scripts that come with Primer3.
Proper citation: Primer3Plus (RRID:SCR_003081) Copy
Can't find your Tool?
We recommend that you click next to the search bar to check some helpful tips on searches and refine your search firstly. Alternatively, please register your tool with the SciCrunch Registry by adding a little information to a web form, logging in will enable users to create a provisional RRID, but it not required to submit.
Welcome to the Kravitz Resources search. From here you can search through a compilation of resources used by Kravitz and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that Kravitz has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on Kravitz then you can log in from here to get additional features in Kravitz such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into Kravitz you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the sources that were queried against in your search that you can investigate further.
Here are the categories present within Kravitz that you can filter your data on
Here are the subcategories present within this category that you can filter your data on
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.